Results 51 to 60 of about 5,295 (219)

Correlation Analysis of Influencing Factors of Autonomous Vehicle Accidents Based on Improved Apriori Algorithm

Journal of Advanced Transportation, Volume 2026, Issue 1, 2026.
The purpose of this study was to explore the risk factors for autonomous vehicle (AV) crashes and their interdependencies. A total of 659 AV crash data were collected between 2018 and July 2024 from AV crash reports published by the California Department of Motor Vehicles.
Tao Wang, Wenzhi Tang, Juncong Chen, Wenwu Chen, Mohammad Rezwan Habib   +4 more
wiley   +1 more source

Mining Correlated High Utility Itemsets in One Phase

IEEE Access, 2020
High-utility itemset mining (HUIM) in transaction databases has been extensively studied to discover interesting itemsets from users' purchase behaviors. With this, business managers can adjust their sale strategies appropriately to increase profit. HUIM
Bay Vo, Le V. Nguyen, Vinh V. Vu, Mi T. H. Lam, Thuy T. M. Duong, Ly T. Manh, Thuy T. T. Nguyen, Loan T. T. Nguyen, Tzung-Pei Hong   +8 more
doaj   +1 more source

FTKHUIM: A Fast and Efficient Method for Mining Top-K High-Utility Itemsets

IEEE Access, 2023
High-utility itemset mining (HUIM) is an important task in the field of knowledge data discovery. The large search space and huge number of HUIs are the consequences of applying HUIM algorithms with an inappropriate user-defined minimum utility threshold
Vinh V. Vu, Mi T. H. Lam, Thuy T. M. Duong, Ly T. Manh, Thuy T. T. Nguyen, Le V. Nguyen, Unil Yun, Vaclav Snasel, Bay Vo   +8 more
doaj   +1 more source

Taming the Triangle: On the Interplays Between Fairness, Interpretability, and Privacy in Machine Learning

Computational Intelligence, Volume 41, Issue 4, August 2025.
ABSTRACT Machine learning techniques are increasingly used for high‐stakes decision‐making, such as college admissions, loan attribution, or recidivism prediction. Thus, it is crucial to ensure that the models learnt can be audited or understood by human users, do not create or reproduce discrimination or bias and do not leak sensitive information ...
Julien Ferry, Ulrich Aïvodji, Sébastien Gambs, Marie‐José Huguet, Mohamed Siala   +4 more
wiley   +1 more source

Mining High Utility Itemsets Based on Pattern Growth without Candidate Generation

Mathematics, 2020
Mining high utility itemsets (HUIs) has been an active research topic in data mining in recent years. Existing HUI mining algorithms typically take two steps: generating candidates and identifying utility values of these candidate itemsets.
Yiwei Liu, Le Wang, Lin Feng, Bo Jin
doaj   +1 more source

A novel transformer health state direct prediction method based on knowledge and data fusion‐driven model

High Voltage, Volume 10, Issue 3, Page 710-725, June 2025.
Abstract Predicting the future health state of a transformer can offer early warning of latent defects and faults within the transformer, thereby facilitating the formulation of power outage maintenance plans and power dispatch strategies. However, existing prediction methods based on the structure of ‘splicing prediction and diagnosis method’ suffer ...
Peng Zhang, Guoliang Zhang, Fei Zhou, Xiaoyu Fan, Yi Zhang, Zexu Du   +5 more
wiley   +1 more source

Data Mining of Infertility and Factors Influencing Its Development: A Finding From a Prospective Cohort Study of RaNCD in Iran

Health Science Reports, Volume 8, Issue 1, January 2025.
ABSTRACT Background and Aims Infertility, as defined by the World Health Organization, is the inability to conceive after 12 months of regular, unprotected intercourse. This study aimed to identify factors influencing infertility by applying data mining techniques, specifically rule‐mining methods, to analyze diverse patient data and uncover relevant ...
Hosna Heydarian, Masoumeh Abbasi, Farid Najafi, Mitra Darbandi   +3 more
wiley   +1 more source

PUC: parallel mining of high-utility itemsets with load balancing on spark

Journal of Intelligent Systems, 2022
Distributed programming paradigms such as MapReduce and Spark have alleviated sequential bottleneck while mining of massive transaction databases. Of significant importance is mining High Utility Itemset (HUI) that incorporates the revenue of the items ...
Brahmavar Anup Bhat, Sheeranalli Venkatarama Harish, Maiya Geetha   +2 more
doaj   +1 more source

A multi‐agent K‐means with case‐based reasoning for an automated quality assessment of software requirement specification

IET Communications, Volume 19, Issue 1, January/December 2025.
This paper proposed an Automated Quality Assessment of SRS (AQA‐SRS) framework by integrating four popular methods which are; NLP, K‐means, MAS, and CBR to assess the quality of SRS documents. The NLP utilize for feature extraction, K‐means for features clustering, MAS for interactive assessment and feature selection decision, and CBR for managing the ...
Mohammed Ahmed Jubair, Salama A. Mostafa, Aida Mustapha, Mohamad Aizi Salamat, Mustafa Hamid Hassan, Mazin Abed Mohammed, Fahad Taha AL‐Dhief   +6 more
wiley   +1 more source

MINING OF HIGH-UTILITY ITEMSETS WITH NEGATIVE UTILITY

JOURNAL OF TECHNOLOGY & INNOVATION, 2020
The goal of the high-utility itemset mining task is to discover combinations of items that yield high profits from transactional databases. HUIM is a useful tool for retail stores to analyze customer behaviors. However, in the real world, items are found with both positive and negative utility values.
Tung N.T, Nguyen Le Van, Trinh Cong Nhut, Tran Van Sang   +3 more
openaire   +1 more source